



import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin


class 	lowerCamelCase__	(       _A							,  unittest.TestCase):



 """simple docstring"""

 a__					: Optional[Any] =  BlenderbotSmallTokenizer
 a__					: List[str] =  False

 def     snake_case_      (    self					:					Optional[Any]      )   ->	Optional[int]:
    super().setUp()

    _A      =       ['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
    _A      =       dict(zip(__lowerCAmelCase			,						range(len(__lowerCAmelCase      )      )      )      )

    _A      =       ['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
    _A      =       {'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

    _A      =       os.path.join(self.tmpdirname			,						VOCAB_FILES_NAMES['''vocab_file''']      )
    _A      =       os.path.join(self.tmpdirname			,						VOCAB_FILES_NAMES['''merges_file''']      )
    with open(self.vocab_file			,						'''w'''			,						encoding='''utf-8'''      ) as fp:
       fp.write(json.dumps(__lowerCAmelCase      ) + '''\n'''      )
    with open(self.merges_file			,						'''w'''			,						encoding='''utf-8'''      ) as fp:
       fp.write('''\n'''.join(__lowerCAmelCase      )      )

 def     snake_case_      (    self					:					List[str]			,						**__lowerCAmelCase					:					Any      )   ->	Any:
    kwargs.update(self.special_tokens_map      )
    return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname			,						**__lowerCAmelCase      )

 def     snake_case_      (    self					:					List[str]			,						__lowerCAmelCase					:					int      )   ->	Optional[Any]:
    _A      =       '''adapt act apte'''
    _A      =       '''adapt act apte'''
    return input_text, output_text

 def     snake_case_      (    self					:					List[Any]      )   ->	int:
    _A      =       BlenderbotSmallTokenizer(self.vocab_file			,						self.merges_file			,						**self.special_tokens_map      )
    _A      =       '''adapt act apte'''
    _A      =       ['''adapt''', '''act''', '''ap@@''', '''te''']
    _A      =       tokenizer.tokenize(__lowerCAmelCase      )
    self.assertListEqual(__lowerCAmelCase			,						__lowerCAmelCase      )

    _A      =       [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

    _A      =       [0, 1, 2, 3, 4, 5]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase      )			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					Dict      )   ->	Any:
    _A      =       BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''      )
    assert tok('''sam'''      ).input_ids == [13_84]
    _A      =       '''I am a small frog.'''
    _A      =       tok([src_text]			,						padding=__lowerCAmelCase			,						truncation=__lowerCAmelCase      )['''input_ids''']
    _A      =       tok.batch_decode(__lowerCAmelCase			,						skip_special_tokens=__lowerCAmelCase			,						clean_up_tokenization_spaces=__lowerCAmelCase      )[0]
    assert src_text != decoded  # I wish it did!
    assert decoded == "i am a small frog ."

 def     snake_case_      (    self					:					Optional[Any]      )   ->	Optional[Any]:
    _A      =       BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''      )
    _A      =       '''I am a small frog .'''
    _A      =       '''.'''
    _A      =       tok(__lowerCAmelCase      )['''input_ids''']
    _A      =       tok(__lowerCAmelCase      )['''input_ids''']

    assert encoded[-1] == encoded_dot[0]









'''simple docstring'''


from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase_					=   Lock()


def     SCREAMING_SNAKE_CASE							(   a_						:				str					,       a_						:				Tuple					,       a_						:				Dict					,       a_						:				Optional[Any]					,       a_						:				str					,       a_						:				Any					,       a_						:				Optional[Any]      ):
  global process_lock

  # we perform n swaps since after n swaps we know we are sorted
  # we *could* stop early if we are sorted already, but it takes as long to
  # find out we are sorted as it does to sort the list with this algorithm
  for i in range(0					,       10      ):
    if (i + position) % 2 == 0 and r_send is not None:
      # send your value to your right neighbor
      process_lock.acquire()
      r_send[1].send(a_      )
      process_lock.release()

      # receive your right neighbor's value
      process_lock.acquire()
      __a								=       rr_cv[0].recv()
      process_lock.release()

      # take the lower value since you are on the left
      __a								=       min(a_					,       a_      )
    elif (i + position) % 2 != 0 and l_send is not None:
      # send your value to your left neighbor
      process_lock.acquire()
      l_send[1].send(a_      )
      process_lock.release()

      # receive your left neighbor's value
      process_lock.acquire()
      __a								=       lr_cv[0].recv()
      process_lock.release()

      # take the higher value since you are on the right
      __a								=       max(a_					,       a_      )
    # after all swaps are performed, send the values back to main
  result_pipe[1].send(a_      )


def     SCREAMING_SNAKE_CASE							(   a_						:				List[str]      ):
  __a								=       []
  __a								=       []
  # initialize the list of pipes where the values will be retrieved
  for _ in arr:
    result_pipe.append(Pipe()      )
  # creates the processes
  # the first and last process only have one neighbor so they are made outside
  # of the loop
  __a								=       Pipe()
  __a								=       Pipe()
  process_array_.append(
      Process(
          target=a_					,       args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])					,       )      )
  __a								=       temp_rs
  __a								=       temp_rr

  for i in range(1					,       len(a_      ) - 1      ):
    __a								=       Pipe()
    __a								=       Pipe()
    process_array_.append(
        Process(
            target=a_					,       args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])					,       )      )
    __a								=       temp_rs
    __a								=       temp_rr

  process_array_.append(
      Process(
          target=a_					,       args=(
              len(a_      ) - 1,
              arr[len(a_      ) - 1],
              temp_ls,
              None,
              temp_lr,
              None,
              result_pipe[len(a_      ) - 1],
          )					,       )      )

  # start the processes
  for p in process_array_:
    p.start()

  # wait for the processes to end and write their values to the list
  for p in range(0					,       len(a_      )      ):
    __a								=       result_pipe[p][0].recv()
    process_array_[p].join()
  return arr


def     SCREAMING_SNAKE_CASE							(   ):
  __a								=       list(range(10					,       0					,       -1      )      )
  print('Initial List'      )
  print(*a_      )
  __a								=       odd_even_transposition(a_      )
  print('Sorted List\n'      )
  print(*a_      )


if __name__ == "__main__":
  main()



